Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

- We present the work on efficient classification of multispectral images using soft computing approach.
- Selection of most discriminative spectral bands and determination of the number of hidden layer neurons are the two most critical issues.
- We proposed a new multiobjective particle swarm optimization based methodology for adaption of neural network structure for pixel classification of Satellite Imagery.
- It simultaneously estimates the most discriminative spectral features and the optimal number of nodes in hidden layer.
- Xie-Beni and β indexes of proposed algorithm are better than MLC and Euclidean Classifier.